Multiuser diversity is a form of selection diversity among users in a wireless communication system that arises from independent fading channels between a base station and multiple users. A variety of multiuser scheduling algorithms have been proposed that take advantage of multiuser diversity for downlink transmissions in multiple-input multiple-output (MIMO) systems. Most of these existing approaches are based on time division multiple access (TDMA). However, due at least in part to the fact that a base station using TDMA can transmit to only one user at a time, the maximum sum-rate achievable by such approaches for MIMO broadcast channels is only a small fraction of the total sum-rate capacity of MIMO broadcast channels.
Other existing scheduling algorithms, such as dirty paper coding (DPC), can achieve MIMO broadcast channel capacity by serving multiple users simultaneously. However, achieving an optimum transmission policy using a scheduling algorithm such as DPC is computationally complex. Further, while low-complexity DPC algorithms have been proposed, such algorithms require perfect knowledge of channel state information (CSI) at the transmitter. However, perfect knowledge of CSI at the transmitter is generally impossible to obtain in practice due to system limitations. Instead, a limited CSI feedback load is generally provided to a base station from users at a finite rate. As the available feedback load of a system decreases, traditional multiuser scheduling algorithms experience a significant reduction of throughput and/or a significant increase in complexity. Accordingly, there exists a need for a low-complexity, high-throughput scheduling algorithm for MIMO broadcast channels with finite rate feedback.